{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,23]],"date-time":"2025-10-23T21:04:23Z","timestamp":1761253463606},"reference-count":19,"publisher":"IEEE","license":[{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/ieeexplore.ieee.org\/Xplorehelp\/downloads\/license-information\/IEEE.html"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2020,4,1]],"date-time":"2020-04-01T00:00:00Z","timestamp":1585699200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2020,4]]},"DOI":"10.1109\/isbi45749.2020.9098737","type":"proceedings-article","created":{"date-parts":[[2020,5,22]],"date-time":"2020-05-22T21:12:08Z","timestamp":1590181928000},"page":"372-376","source":"Crossref","is-referenced-by-count":10,"title":["Spectral Graph Transformer Networks for Brain Surface Parcellation"],"prefix":"10.1109","author":[{"given":"Ran","family":"He","sequence":"first","affiliation":[]},{"given":"Karthik","family":"Gopinath","sequence":"additional","affiliation":[]},{"given":"Christian","family":"Desrosiers","sequence":"additional","affiliation":[]},{"given":"Herve","family":"Lombaert","sequence":"additional","affiliation":[]}],"member":"263","reference":[{"key":"ref10","doi-asserted-by":"publisher","DOI":"10.1109\/TPAMI.2015.2408348"},{"key":"ref11","article-title":"Geodesic convolutional neural networks on Riemannian manifolds","author":"jonathan","year":"0","journal-title":"3dRR-ICCV"},{"key":"ref12","article-title":"Learning shape correspondence with anisotropic convolutional neural networks","author":"boscaini","year":"0","journal-title":"NIPS"},{"key":"ref13","doi-asserted-by":"publisher","DOI":"10.1016\/j.media.2019.03.012"},{"key":"ref14","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-319-19992-4_37"},{"key":"ref15","doi-asserted-by":"publisher","DOI":"10.1007\/978-3-030-20351-1_7"},{"key":"ref16","article-title":"Spatial transformer networks","author":"jaderberg","year":"0","journal-title":"NIPS"},{"key":"ref17","article-title":"Pointnet: Deep learning on point sets for 3d classification and segmentation","author":"qi","year":"0","journal-title":"CVPR"},{"key":"ref18","article-title":"Mindboggling morphometry of human brains","author":"arno","year":"0","journal-title":"PLoS Biology"},{"key":"ref19","article-title":"Graph convolutions on spectral embeddings: Learning of cortical surface data","author":"gopinath","year":"0","journal-title":"NeurIPS Workshop on Medical Imaging"},{"key":"ref4","article-title":"Efficient multi-scale 3D CNN with fully connected CRF for accurate brain lesion segmentation","author":"konstantinos","year":"2017","journal-title":"MedIA"},{"key":"ref3","doi-asserted-by":"publisher","DOI":"10.1109\/TMI.2018.2878669"},{"key":"ref6","doi-asserted-by":"publisher","DOI":"10.1109\/CVPR.2017.576"},{"key":"ref5","doi-asserted-by":"publisher","DOI":"10.1109\/MSP.2017.2693418"},{"key":"ref8","article-title":"Making laplacians commute","author":"bronstein","year":"2013","journal-title":"CoRR"},{"key":"ref7","doi-asserted-by":"publisher","DOI":"10.1109\/TSP.2018.2879624"},{"key":"ref2","article-title":"Unbiased tensor-based morphometry: Improved robustness and sample size estimates for Alzheimer's disease clinical trials","author":"xue","year":"2013","journal-title":"NeuroImage"},{"key":"ref1","article-title":"ODVBA: Optimally-discriminative voxel-based analysis","author":"zhang","year":"2011","journal-title":"TMI"},{"key":"ref9","article-title":"Coupled quasi-harmonic bases","author":"artiom","year":"2013","journal-title":"Computer Graphics Forum"}],"event":{"name":"2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)","start":{"date-parts":[[2020,4,3]]},"location":"Iowa City, IA, USA","end":{"date-parts":[[2020,4,7]]}},"container-title":["2020 IEEE 17th International Symposium on Biomedical Imaging (ISBI)"],"original-title":[],"link":[{"URL":"http:\/\/xplorestaging.ieee.org\/ielx7\/9091448\/9098313\/09098737.pdf?arnumber=9098737","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2022,6,28]],"date-time":"2022-06-28T21:58:15Z","timestamp":1656453495000},"score":1,"resource":{"primary":{"URL":"https:\/\/ieeexplore.ieee.org\/document\/9098737\/"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2020,4]]},"references-count":19,"URL":"https:\/\/doi.org\/10.1109\/isbi45749.2020.9098737","relation":{},"subject":[],"published":{"date-parts":[[2020,4]]}}}